OpenRaiser/Intern-Atlas huggingface dataset:
Towards a Formalism-Based Toolkit for Automotive Applications
Venue: arXiv cs.SE 2013
Year: 2013

The success of a number of projects has been shown to be significantly improved by the use of a formalism. However, there remains an open issue: to what extent can a development process based on a singular formal notation and method succeed. The majority of approaches demonstrate a low level of flexibility by attempting to use a single notation to express all of the different aspects encountered in software development. Often, these approaches leave a number of scalability issues open. We prefer a more eclectic approach. In our experience, the use of a formalism-based toolkit with adequate notations for each development phase is a viable solution. Following this principle, any specific notation is used only where and when it is really suitable and not necessarily over the entire software lifecycle. The approach explored in this article is perhaps slowly emerging in practice - we hope to accelerate its adoption. However, the major challenge is still finding the best way to instantiate it for each specific application scenario. In this work, we describe a development process and method for automotive applications which consists of five phases. The process recognizes the need for having adequate (and tailored) notations (Problem Frames, Requirements State Machine Language, and Event-B) for each development phase as well as direct traceability between the documents produced during each phase. This allows for a stepwise verification/validation of the system under development. The ideas for the formal development method have evolved over two significant case studies carried out in the DEPLOY project.
Novelty Detection Under Multi-Instance Multi-Label Framework
Venue: arXiv cs.LG 2013
Year: 2013

Novelty detection plays an important role in machine learning and signal processing. This paper studies novelty detection in a new setting where the data object is represented as a bag of instances and associated with multiple class labels, referred to as multi-instance multi-label (MIML) learning. Contrary to the common assumption in MIML that each instance in a bag belongs to one of the known classes, in novelty detection, we focus on the scenario where bags may contain novel-class instances. The goal is to determine, for any given instance in a new bag, whether it belongs to a known class or a novel class. Detecting novelty in the MIML setting captures many real-world phenomena and has many potential applications. For example, in a collection of tagged images, the tag may only cover a subset of objects existing in the images. Discovering an object whose class has not been previously tagged can be useful for the purpose of soliciting a label for the new object class. To address this novel problem, we present a discriminative framework for detecting new class instances. Experiments demonstrate the effectiveness of our proposed method, and reveal that the presence of unlabeled novel instances in training bags is helpful to the detection of such instances in testing stage.
Experience of Developing a Meta-Semantic Search Engine
Venue: arXiv cs.IR 2013
Year: 2013

Thinking of todays web search scenario which is mainly keyword based, leads to the need of effective and meaningful search provided by Semantic Web. Existing search engines are vulnerable to provide relevant answers to users query due to their dependency on simple data available in web pages. On other hand, semantic search engines provide efficient and relevant results as the semantic web manages information with well defined meaning using ontology. A Meta-Search engine is a search tool that forwards users query to several existing search engines and provides combined results by using their own page ranking algorithm. SemanTelli is a meta semantic search engine that fetches results from different semantic search engines such as Hakia, DuckDuckGo, SenseBot through intelligent agents. This paper proposes enhancement of SemanTelli with improved snippet analysis based page ranking algorithm and support for image and news search.
Stitched Panoramas from Toy Airborne Video Cameras
Venue: arXiv cs.CV 2013
Year: 2013

Effective panoramic photographs are taken from vantage points that are high. High vantage points have recently become easier to reach as the cost of quadrotor helicopters has dropped to nearly disposable levels. Although cameras carried by such aircraft weigh only a few grams, their low-quality video can be converted into panoramas of high quality and high resolution. Also, the small size of these aircraft vastly reduces the risks inherent to flight.
The Untold Story of the Clones: Content-agnostic Factors that Impact YouTube Video Popularity
Venue: arXiv cs.SI 2013
Year: 2013

Video dissemination through sites such as YouTube can have widespread impacts on opinions, thoughts, and cultures. Not all videos will reach the same popularity and have the same impact. Popularity differences arise not only because of differences in video content, but also because of other "content-agnostic" factors. The latter factors are of considerable interest but it has been difficult to accurately study them. For example, videos uploaded by users with large social networks may tend to be more popular because they tend to have more interesting content, not because social network size has a substantial direct impact on popularity. In this paper, we develop and apply a methodology that is able to accurately assess, both qualitatively and quantitatively, the impacts of various content-agnostic factors on video popularity. When controlling for video content, we observe a strong linear "rich-get-richer" behavior, with the total number of previous views as the most important factor except for very young videos. The second most important factor is found to be video age. We analyze a number of phenomena that may contribute to rich-get-richer, including the first-mover advantage, and search bias towards popular videos. For young videos we find that factors other than the total number of previous views, such as uploader characteristics and number of keywords, become relatively more important. Our findings also confirm that inaccurate conclusions can be reached when not controlling for content.
Implementing program extraction from CL1-proofs
Venue: arXiv cs.LO 2013
Year: 2013

Computability logic (CoL) is a formal theory of interactive computation. It understands computational problems as games played by two players: a machine and its environment, uses logical formalism to describe valid principles of computability and formulas to represent computational problems. Logic CL1 is a deductive system for a fragment of CoL. The logical vocabulary contains all of the operators of classical logic and choice operators, the atoms represent elementary games i.e. predicates of classical logic. In this paper, we present a program that takes a CL1-proof of an arbitrary formula $F$, and extract a winning strategy for $F$ from that proof then play $F$ using that strategy. We hope this paper would provide a starting point for further work in program extraction of the CoL-based arithmetic and other CoL-based applied systems.
Color and Shape Content Based Image Classification using RBF Network and PSO Technique: A Survey
Venue: arXiv cs.CV 2013
Year: 2013

The improvement of the accuracy of image query retrieval used image classification technique. Image classification is well known technique of supervised learning. The improved method of image classification increases the working efficiency of image query retrieval. For the improvements of classification technique we used RBF neural network function for better prediction of feature used in image retrieval.Colour content is represented by pixel values in image classification using radial base function(RBF) technique. This approach provides better result compare to SVM technique in image representation.Image is represented by matrix though RBF using pixel values of colour intensity of image. Firstly we using RGB colour model. In this colour model we use red, green and blue colour intensity values in matrix.SVM with partical swarm optimization for image classification is implemented in content of images which provide better Results based on the proposed approach are found encouraging in terms of color image classification accuracy.
Deterministic Approximate Counting for Degree-$2$ Polynomial Threshold Functions
Venue: arXiv cs.CC 2013
Year: 2013

We give a {\em deterministic} algorithm for approximately computing the fraction of Boolean assignments that satisfy a degree-$2$ polynomial threshold function. Given a degree-2 input polynomial $p(x_1,\dots,x_n)$ and a parameter $\eps > 0$, the algorithm approximates \[ \Pr_{x \sim \{-1,1\}^n}[p(x) \geq 0] \] to within an additive $\pm \eps$ in time $\poly(n,2^{\poly(1/\eps)})$. Note that it is NP-hard to determine whether the above probability is nonzero, so any sort of multiplicative approximation is almost certainly impossible even for efficient randomized algorithms. This is the first deterministic algorithm for this counting problem in which the running time is polynomial in $n$ for $\eps= o(1)$. For "regular" polynomials $p$ (those in which no individual variable's influence is large compared to the sum of all $n$ variable influences) our algorithm runs in $\poly(n,1/\eps)$ time. The algorithm also runs in $\poly(n,1/\eps)$ time to approximate $\Pr_{x \sim N(0,1)^n}[p(x) \geq 0]$ to within an additive $\pm \eps$, for any degree-2 polynomial $p$. As an application of our counting result, we give a deterministic FPT multiplicative $(1 \pm \eps)$-approximation algorithm to approximate the $k$-th absolute moment $\E_{x \sim \{-1,1\}^n}[|p(x)^k|]$ of a degree-2 polynomial. The algorithm's running time is of the form $\poly(n) \cdot f(k,1/\eps)$.
Theories of Hypergraph-Graph (HG(2)) Data Structure
Venue: arXiv cs.DS 2013
Year: 2013

Current paper introduces a Hypergraph Graph model of data storage which can be represented as a hybrid data structure based on Hypergraph and Graph. The pro-posed data structure is claimed to realize complex combinatorial structures. The formal definition of the data structure is presented along with the proper justification from real world scenarios. The paper reports some elementary concepts of Hypergraph and presents theoretical aspects of the proposed data structure including the concepts of Path, Cycle etc. The detailed analysis of weighted HG 2 is presented along with discussions on Cost involved with HG 2 paths.
Programming with Permissions in Mezzo
Venue: arXiv cs.PL 2013
Year: 2013

We present Mezzo, a typed programming language of ML lineage. Mezzo is equipped with a novel static discipline of duplicable and affine permissions, which controls aliasing and ownership. This rules out certain mistakes, including representation exposure and data races, and enables new idioms, such as gradual initialization, memory re-use, and (type)state changes. Although the core static discipline disallows sharing a mutable data structure, Mezzo offers several ways of working around this restriction, including a novel dynamic ownership control mechanism which we dub "adoption and abandon".
The ins and outs of iteration in Mezzo
Venue: arXiv cs.PL 2013
Year: 2013

This is a talk proposal for HOPE 2013. Using iteration over a collection as a case study, we wish to illustrate the strengths and weaknesses of the prototype programming language Mezzo.
List decoding - random coding exponents and expurgated exponents
Venue: arXiv cs.IT 2013
Year: 2013

Some new results are derived concerning random coding error exponents and expurgated exponents for list decoding with a deterministic list size $L$. Two asymptotic regimes are considered, the fixed list-size regime, where $L$ is fixed independently of the block length $n$, and the exponential list-size, where $L$ grows exponentially with $n$. We first derive a general upper bound on the list-decoding average error probability, which is suitable for both regimes. This bound leads to more specific bounds in the two regimes. In the fixed list-size regime, the bound is related to known bounds and we establish its exponential tightness. In the exponential list-size regime, we establish the achievability of the well known sphere packing lower bound. Relations to guessing exponents are also provided. An immediate byproduct of our analysis in both regimes is the universality of the maximum mutual information (MMI) list decoder in the error exponent sense. Finally, we consider expurgated bounds at low rates, both using Gallager's approach and the Csiszár-Körner-Marton approach, which is, in general better (at least for $L=1$). The latter expurgated bound, which involves the notion of {\it multi-information}, is also modified to apply to continuous alphabet channels, and in particular, to the Gaussian memoryless channel, where the expression of the expurgated bound becomes quite explicit.
Web Mining Techniques in E-Commerce Applications
Venue: arXiv cs.IR 2013
Year: 2013

Today web is the best medium of communication in modern business. Many companies are redefining their business strategies to improve the business output. Business over internet provides the opportunity to customers and partners where their products and specific business can be found. Nowadays online business breaks the barrier of time and space as compared to the physical office. Big companies around the world are realizing that e-commerce is not just buying and selling over Internet, rather it improves the efficiency to compete with other giants in the market. For this purpose data mining sometimes called as knowledge discovery is used. Web mining is data mining technique that is applied to the WWW. There are vast quantities of information available over the Internet.
A local Gaussian filter and adaptive morphology as tools for completing partially discontinuous curves
Venue: arXiv cs.GR 2013
Year: 2013

This paper presents a method for extraction and analysis of curve--type structures which consist of disconnected components. Such structures are found in electron--microscopy (EM) images of metal nanograins, which are widely used in the field of nanosensor technology. The topography of metal nanograins in compound nanomaterials is crucial to nanosensor characteristics. The method of completing such templates consists of three steps. In the first step, a local Gaussian filter is used with different weights for each neighborhood. In the second step, an adaptive morphology operation is applied to detect the endpoints of curve segments and connect them. In the last step, pruning is employed to extract a curve which optimally fits the template.
Weak Parity
Venue: arXiv cs.CC 2013
Year: 2013

We study the query complexity of Weak Parity: the problem of computing the parity of an n-bit input string, where one only has to succeed on a 1/2+eps fraction of input strings, but must do so with high probability on those inputs where one does succeed. It is well-known that n randomized queries and n/2 quantum queries are needed to compute parity on all inputs. But surprisingly, we give a randomized algorithm for Weak Parity that makes only O(n/log^0.246(1/eps)) queries, as well as a quantum algorithm that makes only O(n/sqrt(log(1/eps))) queries. We also prove a lower bound of Omega(n/log(1/eps)) in both cases; and using extremal combinatorics, prove lower bounds of Omega(log n) in the randomized case and Omega(sqrt(log n)) in the quantum case for any eps>0. We show that improving our lower bounds is intimately related to two longstanding open problems about Boolean functions: the Sensitivity Conjecture, and the relationships between query complexity and polynomial degree.
Boosting the Basic Counting on Distributed Streams
Venue: arXiv cs.DS 2013
Year: 2013

We revisit the classic basic counting problem in the distributed streaming model that was studied by Gibbons and Tirthapura (GT). In the solution for maintaining an $(ε,δ)$-estimate, as what GT's method does, we make the following new contributions: (1) For a bit stream of size $n$, where each bit has a probability at least $γ$ to be 1, we exponentially reduced the average total processing time from GT's $Θ(n \log(1/δ))$ to $O((1/(γε^2))(\log^2 n) \log(1/δ))$, thus providing the first sublinear-time streaming algorithm for this problem. (2) In addition to an overall much faster processing speed, our method provides a new tradeoff that a lower accuracy demand (a larger value for $ε$) promises a faster processing speed, whereas GT's processing speed is $Θ(n \log(1/δ))$ in any case and for any $ε$. (3) The worst-case total time cost of our method matches GT's $Θ(n\log(1/δ))$, which is necessary but rarely occurs in our method. (4) The space usage overhead in our method is a lower order term compared with GT's space usage and occurs only $O(\log n)$ times during the stream processing and is too negligible to be detected by the operating system in practice. We further validate these solid theoretical results with experiments on both real-world and synthetic data, showing that our method is faster than GT's by a factor of several to several thousands depending on the stream size and accuracy demands, without any detectable space usage overhead. Our method is based on a faster sampling technique that we design for boosting GT's method and we believe this technique can be of other interest.
Improving Texture Categorization with Biologically Inspired Filtering
Venue: arXiv cs.CV 2013
Year: 2013

Within the domain of texture classification, a lot of effort has been spent on local descriptors, leading to many powerful algorithms. However, preprocessing techniques have received much less attention despite their important potential for improving the overall classification performance. We address this question by proposing a novel, simple, yet very powerful biologically-inspired filtering (BF) which simulates the performance of human retina. In the proposed approach, given a texture image, after applying a DoG filter to detect the "edges", we first split the filtered image into two "maps" alongside the sides of its edges. The feature extraction step is then carried out on the two "maps" instead of the input image. Our algorithm has several advantages such as simplicity, robustness to illumination and noise, and discriminative power. Experimental results on three large texture databases show that with an extremely low computational cost, the proposed method improves significantly the performance of many texture classification systems, notably in noisy environments. The source codes of the proposed algorithm can be downloaded from https://sites.google.com/site/nsonvu/code.
Knowing Whether
Venue: arXiv cs.AI 2013
Year: 2013

Knowing whether a proposition is true means knowing that it is true or knowing that it is false. In this paper, we study logics with a modal operator Kw for knowing whether but without a modal operator K for knowing that. This logic is not a normal modal logic, because we do not have Kw (phi -> psi) -> (Kw phi -> Kw psi). Knowing whether logic cannot define many common frame properties, and its expressive power less than that of basic modal logic over classes of models without reflexivity. These features make axiomatizing knowing whether logics non-trivial. We axiomatize knowing whether logic over various frame classes. We also present an extension of knowing whether logic with public announcement operators and we give corresponding reduction axioms for that. We compare our work in detail to two recent similar proposals.
On an Algorithm for Obtaining All Binary Matrices of Special Class Related to V. E. Tarakanov's Formula
Venue: arXiv cs.DS 2013
Year: 2013

An algorithm for obtaining all n\times n binary matrices having exactly 2 units in every row and every column is described in the paper. After analysing the work of the algorithm a formula for calculating the number of these matrices has been obtained. This formula is known and has been obtained using other methods, which by their nature are purely analytical and not constructive. Thus a new, constructive proof of this known formula has been obtained.
Analyzing Flowgraphs with ATL
Venue: arXiv cs.SE 2013
Year: 2013

This paper presents a solution to the Flowgraphs case study for the Transformation Tool Contest 2013 (TTC 2013). Starting from Java source code, we execute a chain of model transformations to derive a simplified model of the program, its control flow graph and its data flow graph. Finally we develop a model transformation that validates the program flow by comparing it with a set of flow specifications written in a domain specific language. The proposed solution has been implemented using ATL.
Solving the Flowgraphs Case with Eclectic
Venue: arXiv cs.SE 2013
Year: 2013

This paper presents a solution for the Flow Graphs case of the Transformation Tool Contest 2013, using the Eclectic model transformation tool. The solution makes use of several languages of Eclectic, showing how it is possible to combine them to address a non-trivial transformation problem in a concise and modulary way.
A Solution to the Flowgraphs Case Study using Triple Graph Grammars and eMoflon
Venue: arXiv cs.SE 2013
Year: 2013

After 20 years of Triple Graph Grammars (TGGs) and numerous actively maintained implementations, there is now a need for challenging examples and success stories to show that TGGs can be used for real-world bidirectional model transformations. Our primary goal in recent years has been to increase the expressiveness of TGGs by providing a set of pragmatic features that allow a controlled fallback to programmed graph transformations and Java. Based on the Flowgraphs case study of the Transformation Tool Contest (TTC 2013), we present (i) attribute constraints used to express complex bidirectional attribute manipulation, (ii) binding expressions for specifying arbitrary context relationships, and (iii) post-processing methods as a black box extension for TGG rules. In each case, we discuss the enabled trade-off between guaranteed formal properties and expressiveness. Our solution, implemented with our metamodelling and model transformation tool eMoflon (www.emoflon.org), is available as a virtual machine hosted on Share.
Abmash: Mashing Up Legacy Web Applications by Automated Imitation of Human Actions
Venue: arXiv cs.SE 2013
Year: 2013

Many business web-based applications do not offer applications programming interfaces (APIs) to enable other applications to access their data and functions in a programmatic manner. This makes their composition difficult (for instance to synchronize data between two applications). To address this challenge, this paper presents Abmash, an approach to facilitate the integration of such legacy web applications by automatically imitating human interactions with them. By automatically interacting with the graphical user interface (GUI) of web applications, the system supports all forms of integrations including bi-directional interactions and is able to interact with AJAX-based applications. Furthermore, the integration programs are easy to write since they deal with end-user, visual user-interface elements. The integration code is simple enough to be called a "mashup".